Characterization of a G2M checkpoint-related gene model and subtypes associated with immunotherapy response for clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) presents challenges in early diagnosis and effective treatment. In this study, we aimed to establish a prognostic model based on G2M checkpoint-related genes and identify associated clusters in ccRCC through clinical bioinformatic analysis and experimental validation. Utilizing a single-cell RNA dataset (GSE159115) and bulk-sequencing data from The Cancer Genome Atlas (TCGA) database, we analyzed the G2M checkpoint pathway in ccRCC. Differential expression analysis identified 45 genes associated with the G2M checkpoint, leading to the construction of a predictive model with four key genes (E2F2, GTSE1, RAD54L, and UBE2C). The model demonstrated reliable predictive ability for 1-, 3-, and 5-year overall survival, with AUC values of 0.794, 0.790, and 0.794, respectively. Patients in the high-risk group exhibited a worse prognosis, accompanied by significant differences in immune cell infiltration, immune function, TIDE and IPS scores, and drug sensitivities. Two clusters of ccRCC were identified using the "ConsensusClusterPlus" package, cluster 1 exhibited a worse survival rate and was resistant to chemotherapeutic drugs of Axitinib, Erlotinib, Pazopanib, Sunitinib, and Temsirolimus, but not Sorafenib. Targeted experiments on RAD54L, a gene involved in DNA repair processes, revealed its crucial role in inhibiting proliferation, invasion, and migration in 786-O cells. In conclusion, our study offers valuable insights into the molecular mechanisms underlying ccRCC, identifying potential prognostic genes and molecular subtypes associated with the G2M checkpoint. These findings hold promise for guiding personalized treatment strategies in the management of ccRCC.

piRNA-1742 promotes renal cell carcinoma malignancy by regulating USP8 stability through binding to hnRNPU and thereby inhibiting MUC12 ubiquitination.

Accumulating studies have confirmed that PIWI-interacting RNAs (piRNAs) are considered epigenetic effectors in cancer. We performed piRNA microarray expression analysis on renal cell carcinoma (RCC) tumor tissues and paired normal tissues and performed a series of in vivo and in vitro experiments to explore piRNAs associated with RCC progression and investigate their functional mechanisms. We found that piR-1742 was highly expressed in RCC tumors and that patients with high piR-1742 expression had a poor prognosis. Inhibition of piR-1742 significantly reduced tumor growth in RCC xenograft and organoid models. Mechanistically, piRNA-1742 regulates the stability of USP8 mRNA by binding directly to hnRNPU, which acts as a deubiquitinating enzyme that inhibits the ubiquitination of MUC12 and promotes the development of malignant RCC. Subsequently, nanotherapeutic systems loaded with piRNA-1742 inhibitors were found to effectively inhibit the metastasis and growth of RCC in vivo. Therefore, this study highlights the functional importance of piRNA-related ubiquitination in RCC and demonstrates the development of a related nanotherapeutic system, possibly contributing to the development of therapeutic approaches for RCC.

Molecular subtypes, tumor microenvironment infiltration characterization and prognosis model based on cuproptosis in bladder cancer.

Cuproptosis is a kind of cell death dependent on copper. We aimed to explore the functions of the cuproptosis in the tumor microenvironment (TME) and construct a cuproptosis-related prognosis signature in bladder cancer (BCa). Using BCa patients in the public cohort, the cuproptosis-related molecular subtypes and cuproptosis-related prognosis signature were developed. Three cuproptosis-related molecular subtypes, with different prognoses and TME characteristics, were identified in BCa. The cuproptosis-related prognosis signature can divide patients into high- and low-risk groups with different prognoses, TME characteristics, chemotherapeutic drug susceptibility and immunotherapeutic response. Low risk group patients had a favored prognosis and response to immunotherapy. The dysregulation of cuproptosis-related genes expression levels was validated in multiple BCa cells using in vitro experiments. Cuproptosis has an important role in the tumor progression and the characterization of TME in BCa. The cuproptosis-related prognosis signature is a useful biomarker that can reflect the prognosis, TME characteristics, immunotherapeutic response and chemotherapeutic drug susceptibility in BCa patients.

Development of a Molecular-Subtype-Associated Immune Prognostic Signature That Can Be Recognized by MRI Radiomics Features in Bladder Cancer.

Background: Bladder cancer (BLCA) is highly heterogeneous with distinct molecular subtypes. This research aimed to investigate the heterogeneity of different molecular subtypes from a tumor microenvironment perspective and develop a molecular-subtype-associated immune prognostic signature that can be recognized by MRI radiomics features. Methods: Individuals with BLCA in The Cancer Genome Atlas (TCGA) and IMvigor210 were classified into luminal and basal subtypes according to the UNC classification. The proportions of tumor-infiltrating immune cells (TIICs) were examined using The Cell Type Identification by Estimating Relative Subsets of RNA Transcripts algorithm. Immune-linked genes that were expressed differentially between luminal and basal subtypes and associated with prognosis were selected to develop the immune prognostic signature (IPS) and utilized for the classification of the selected individuals into low- and high-risk groups. Functional enrichment analysis (GSEA) was performed on the IPS. The data from RNA-sequencing and MRI images of 111 BLCA samples in our center were utilized to construct a least absolute shrinkage and selection operator (LASSO) model for the prediction of patients' IPSs. Results: Half of the TIICs showed differential distributions between the luminal and basal subtypes. IPS was highly associated with molecular subtypes, critical immune checkpoint gene expression, prognoses, and immunotherapy response. The prognostic value of the IPS was further verified through several validation data sets (GSE32894, GSE31684, GSE13507, and GSE48277) and meta-analysis. GSEA revealed that some oncogenic pathways were co-enriched in the group at high risk. A novel performance of a LASSO model developed as per ten radiomics features was achieved in terms of IPS prediction in both the validation (area under the curve (AUC): 0.810) and the training (AUC: 0.839) sets. Conclusions: Dysregulation of TIICs contributed to the heterogeneity between the luminal and basal subtypes. The IPS can facilitate molecular subtyping, prognostic evaluation, and personalized immunotherapy. A LASSO model developed as per the MRI radiomics features can predict the IPSs of affected individuals.

Metabolic-associated signature and hub genes associated with immune microenvironment and prognosis in bladder cancer.

The relationship between metabolism and immune microenvironment remains to be studied in bladder cancer (BCa). We aimed to construct a metabolic-associated signature for prognostic prediction and investigate its relationship with the immune microenvironment in BCa. The RNA expression of metabolism associated genes was obtained from a combined data set including The Cancer Genome Atlas, GSE48075, and GSE13507 to divide BCa patients into different clusters. A metabolic-associated signature was constructed using the differentially expressed genes between clusters in the combined data set and validated in the IMvigor210 trial and our center. The composition of tumor-infiltrating immune cells (TIICs) was evaluated using the single-sample Gene Set Variation Analysis. BCa patients in Cluster A or high-risk level were associated with advanced clinicopathological features and poor survival outcomes. The percentage of high-risk patients was significantly lower in patients responding to anti-PD-L1 treatment. Compared with low-risk patients, the IC50 values of cisplatin and gemcitabine were significantly lower in high-risk patients. Thiosulfate transferase (TST) and S100A16 were significantly associated with clinicopathological features and prognosis. Downregulation of TST promoted BCa cell invasion, migration, and epithelial-to-mesenchymal transition, which are inhibited by downregulation of S100A16. CD8 + T cells, neutrophils, and dendritic cells had higher infiltration in the TST low-level and the S100A16 high-level. Furthermore, loss of function TST and S100A16 significantly affected the expression of PD-L1 and CD47. The metabolic-associated signature can stratify BCa patients into distinct risk levels with different immunotherapeutic susceptibility and survival outcomes. Metabolism disorder promoted the dysregulation of immune microenvironment, thus contributing to immunosuppression.

CD8A as a Prognostic and Immunotherapy Predictive Biomarker Can Be Evaluated by MRI Radiomics Features in Bladder Cancer.

As an important member of T cytotoxic pathway-related genes, CD8a molecule (CD8A) may be a useful biomarker of immunotherapeutic response and immune cell infiltration. We aimed to investigate the clinical predictive value of CD8A in prognosis and tumor microenvironment (TME) and preoperatively predict the expression of CD8A using radiogenomics in bladder cancer (BCa). Among 12 T cytotoxic pathway-related genes, CD8A was a novel protective gene and had the highest correlations with T cells and Macrophages M1 in BCa. In advanced cancer patients treated with immunotherapy, low CD8A expression was associated with immunotherapeutic failure and poor survival outcomes. CD8A expression was highly related to tumor mutation burden, critical immune checkpoint genes and several types of tumor-infiltrating immune cells, predicting effective response to immunotherapy. The preoperative MRI radiomics features and RNA-sequence data of 111 BCa samples were used to develop a radiomics signature that achieved good performance in the prediction of CD8A expression in both the training (area under curve (AUC): 0.857) and validation sets (AUC: 0.844). CD8A is a novel indicator for predicting the prognosis and immunotherapeutic response in BCa. A radiomics signature has the potential to preoperatively predict the expression of CD8A in BCa patients.

PHGDH Inhibits Ferroptosis and Promotes Malignant Progression by Upregulating SLC7A11 in Bladder Cancer.

Background: Bladder cancer (BCa) is a prevalent urologic malignancy that shows a poor prognosis. Abnormal metabolism and its key genes play a critical role in BCa progression. In this study, the role played by PhosphoGlycerol Dehydrogenase (PHGDH), an important molecule of serine metabolism, was investigated with regard to the regulation of ferroptosis in BCa. Methods: The BCa tissues of 90 patients were analyzed by RNA-sequencing for differential pathways and genes. Western blot, qPCR, and IHC were used to determine PHGDH expression in the cell lines (in vitro) and patient tissues (in vivo). R software was used to analyze PHGDH expression, prognosis, and PHGDH+SLC7A11 score. The biological functions of PHGDH were examined through organoids, and in vitro and in vivo experiments. C11 probes, electron microscopy, and ferroptosis inhibitors/ inducers were used to detect cellular ferroptosis levels. Protein profiling, co-IP, and RIP assays were used to screen proteins that might bind to PHGDH. PHGDH-targeted inhibitor NCT-502 was used to evaluate its effect on BCa cells. Results: PHGDH was highly expressed in patients with BCa. Knock-down of PHGDH promoted ferroptosis, while the decreased proliferation of BCa cells. Additionally, PHGDH knock-down downregulated the expression of SLC7A11. Co-IP and mass spectrometry experiments indicate that PHGDH binds to PCBP2, an RNA-binding protein, and inhibits its ubiquitination degradation. PCBP2 in turn stabilizes SLC7A11 mRNA and increases its expression. NCT-502, a PHGDH inhibitor, promotes ferroptosis and inhibits tumor progression in BCa. The PHGDH+ SLC7A11 score was significantly correlated with patient prognosis. Conclusions: To conclude, the PHGDH, via interaction with PCBP2, upregulates SLC7A11 expression. This inhibits ferroptosis and promotes the malignant progression of BCA. The results of this study indicated that NCT-502 could serve as a therapeutic strategy for BCa.

Urological cancer organoids, patients' avatars for precision medicine: past, present and future.

Urological cancers are common malignant cancers worldwide, with annually increasing morbidity and mortality rates. For decades, two-dimensional cell cultures and animal models have been widely used to study the development and underlying molecular mechanisms of urological cancers. However, they either fail to reflect cancer heterogeneity or are time-consuming and labour-intensive. The recent emergence of a three-dimensional culture model called organoid has the potential to overcome the shortcomings of traditional models. For example, organoids can recapitulate the histopathological and molecular diversity of original cancer and reflect the interaction between cancer and surrounding cells or stroma by simulating tumour microenvironments. Emerging evidence suggests that urine-derived organoids can be generated, which could be a novel non-invasive liquid biopsy method that provides new ideas for clinical precision therapy. However, the current research on organoids has encountered some bottlenecks, such as the lack of a standard culture process, the need to optimize the culture medium and the inability to completely simulate the immune system in vivo. Nonetheless, cell co-culture and organoid-on-a-chip have significant potential to solve these problems. In this review, the latest applications of organoids in drug screening, cancer origin investigation and combined single-cell sequencing are illustrated. Furthermore, the development and application of organoids in urological cancers and their challenges are summarised.

Transfection with Plasmid-Encoding lncRNA-SLERCC nanoparticle-mediated delivery suppressed tumor progression in renal cell carcinoma.

BACKGROUND: The accumulating evidence confirms that long non-coding RNAs (lncRNAs) play a critical regulatory role in the progression of renal cell carcinoma (RCC). But, the application of lncRNAs in gene therapy remains scarce. Here, we investigated the efficacy of a delivery system by introducing the plasmid-encoding tumor suppressor lncRNA-SLERCC (SLERCC) in RCC cells. METHODS: We performed lncRNAs expression profiling in paired cancer and normal tissues through microarray and validated in our clinical data and TCGA dataset. The Plasmid-SLERCC@PDA@MUC12 nanoparticles (PSPM-NPs) were tested in vivo and in vitro, including cellular uptake, entry, CCK-8 assay, tumor growth inhibition, histological assessment, and safety evaluations. Furthermore, experiments with nude mice xenografts model were performed to evaluate the therapeutic effect of PSPM-NPs nanotherapeutic system specific to the SLERCC. RESULTS: We found that the expression of SLERCC was downregulated in RCC tissues, and exogenous upregulation of SLERCC could suppress metastasis of RCC cells. Furthermore, high expression DNMT3A was recruited at the SLERCC promoter, which induced aberrant hypermethylation, eventually leading to downregulation of SLERCC expression in RCC. Mechanistically, SLERCC could directly bind to UPF1 and exert tumor-suppressive effects through the Wnt/ß-catenin signaling pathway, thereby inhibiting progression and metastasis in RCC. Subsequently, the PSPM-NPs nanotherapeutic system can effectively inhibit the growth of RCC metastases in vivo. CONCLUSIONS: Our findings suggested that SLERCC is a promising therapeutic target and that plasmid-encapsulated nanomaterials targeting transmembrane metastasis markers may open a new avenue for the treatment in RCC.

Gender dimorphism in survival of patients with lymph node metastasis of bladder cancer.

Background: The effect of gender on the prognosis of bladder cancer (BCa) in different metastatic sites is insufficiently understood. We aimed to assess the impact and potential mechanisms of a combination of gender dimorphism and BCa metastasis sites on the risk of death. Methods: Independent predictors of overall survival and cancer-specific survival were analyzed after stratification by gender and metastasis sites from the Surveillance, Epidemiology, and End Results database. Furthermore, gender-differentially expressed genes (DEGs) and function-enriched annotations for patients with lymph node metastasis (LNM) were identified from The Cancer Genome Atlas (TCGA) database. A gender-associated signature was constructed in TCGA and validated in the IMvigor210 trial, and the magnetic resonance imaging-based radiomics signature was developed in our center to predict the gender-associated signature. Results: In patients with metastatic BCa, the most common site of metastasis is bone in men and lung in women. Moreover, stratified by sex, LNM had a better prognosis in men than visceral metastasis, which was not observed in female. Similarly, stratified by the metastasis site, the prognosis of men in patients with LNM is better than that of women, which was not observed in visceral metastasis patients. Enrichment of DEGs between sexes in patients with LNM may be related to metastasis and tumor immunity, especially the role of neutrophils. Moreover, the gender-associated signature is related to the clinicopathological characteristics of patients, and patients in the high-risk group had worse survival outcomes, and higher susceptibility to cisplatin, docetaxel, camptothecin, and paclitaxel. A nomogram combined with the signature and clinical staging showed significant predictive power in survival prediction. Furthermore, patients with high radiomics scores had a strong tendency for high-risk group. Conclusion: These results may improve the understanding of the differences in tumor biology between sexes and thus provide additional evidence for individualized treatment in BCa.

Causes of Death after Prostate Cancer Diagnosis: A Population-Based Study.

Background: Mortality from noncancer causes in patients with prostate cancer (PCa) is unclear. This study assesses the causes and risks of noncancer death with each follow-up time period after PCa diagnosis. Methods: Data from the Surveillance, Epidemiology, and End Results (SEER) program were analyzed for noncancer causes of death in PCa patients from 2000 to 2016. The standard mortality ratio (SMR) was calculated for noncancer mortality. Results: Altogether, 752,352 patients with PCa were identified, and 180,862 (24.0%) died during follow-up. The largest proportion of deaths from noncancer causes (36%) occurred within 5 to 10 years after diagnosis. The most common causes of noncancer death are cardiovascular and cerebrovascular diseases and chronic obstructive pulmonary disease (COPD). Compared with the general age-matched male population, patients with PCa had a higher risk of death from any noncancer cause within 5 years, in particular other infectious diseases and suicide and self-inflicted injury. However, the risk of death from noncancer causes of PCa for more than 5 years is lower, except for Alzheimer's disease and hypertension from 5 to 10 years after diagnosis. In addition, the risk of death from noncancer causes was influenced by treatment, ethnicity, and staging differences. In particular, compared with the general population, many noncancer causes of death have higher risk of death in patients with or without treatment within 1 to 5 years after diagnosis, whereas patients undergoing radical prostatectomy (RP) with or without radiotherapy (RT) or chemotherapy (CTx) are not at high risk of death from COPD, pneumonia and influenza, nephritis, nephrotic syndrome and nephrosis, septicemia, and atherosclerosis. Conclusion: The risk of death from noncancer causes gradually decreased in all patients with PCa during each follow-up period after diagnosis In addition, the risk of dying from noncancer causes are influenced by differences in stage, ethnicity, and treatment. In particular, patients undergoing RP±RT/CTx and RT/CTx have a lower risk of death compared to the general population. These findings provide important implications for the healthcare management of patients with PCa.

Recent Trends in the Incidence of Clear Cell Adenocarcinoma and Survival Outcomes: A SEER Analysis.

Background: Clear cell adenocarcinoma (CCA) is considered a relatively rare tumor with a glycogen-rich phenotype. The prognosis of CCA patients is unclear. In this study, recent trends in the epidemiological and prognostic factors of CCA were comprehensively investigated. Methods: Patients with CCA from years 2000 to 2016 were identified from the Surveillance, Epidemiological, and End Results (SEER) database. Relevant population data were used to analyze the rates age-adjusted incidence, age-standardized 3-year and 5-year relative survivals, and overall survival (OS). Results: The age-adjusted incidence of CCA increased 2.7-fold from the year 2000 (3.3/100,000) to 2016 (8.8/100,000). This increase occurred across all ages, races, stages, and grades. Of all these subgroups, the increase was largest in the grade IV group. The age-standardized 3-year and 5-year relative survivals increased during this study period, rising by 9.1% and 9.5% from 2000 to 2011, respectively. Among all the stages and grades, the relative survival increase was greatest in the grade IV group. According to multivariate analysis of all CCA patients, predictors of OS were: age, gender, year of diagnosis, marital status, race, grade, stage, and primary tumor site (P < 0.001). The OS of all CCA patients during the period 2008 to 2016 was significantly higher than that from 2000 to 2007 (P < 0.001). Conclusions: The incidence of CCA and survival of these patients improved over time. In particular, the highest increases were reported for grade IV CCA, which may be due to an earlier diagnosis and improved treatment.

Sulfatase 2 Affects Polarization of M2 Macrophages through the IL-8/JAK2/STAT3 Pathway in Bladder Cancer.

Sulfatase 2 (SULF2) affects the occurrence and development of cancer by regulating HSPG-binding factors. However, the mechanism of SULF2 in bladder cancer (BCa) is unknown. To determine this, we analyzed the RNA sequencing of 90 patients with BCa. The results showed that the expression of SULF2 was closely related to the prognosis of BCa. Moreover, in vivo and in vitro experiments revealed that SULF2 promotes tumor proliferation and invasion. Furthermore, using a mouse orthotopic BCa model and flow cytometric analysis, we identified that SULF2 affects the polarization of macrophages. Mechanism studies clarified that SULF2 promoted the release of HSPG-binding factors, such as IL-8, in the microenvironment through ß-catenin. Meanwhile, IL-8 activated the JAK2/STAT3 pathway of macrophages to promote the expression of CD163 and CD206, thereby regulating the polarization of macrophages to the M2-type. Conclusively, these results indicate that SULF2 plays an important role in regulating the microenvironment of BCa and promotes the polarization of macrophages to the M2-type by secreting IL-8, which further deepens the malignant progression of BCa.

The development and assessment of a predicting nomogram for the recovery of immediate urinary continence following laparoscopic radical prostatectomy.

Purpose: This study aimed to develop a nomogram to predict the recovery of immediate urinary continence in laparoscopic radical prostatectomy (LRP) patients. Methods: A prediction model was developed based on a dataset of 154 LRP patients. Immediate urinary continence was defined as free from using pads within 7 days after the removal of the urinary catheter. The least absolute shrinkage and selection operator regression (LASSO) model was applied to screen the features. Multivariate logistic regression analysis was used to establish prediction model integrating the features selected from the LASSO regression analysis. Receiver operating curve (ROC), calibration and decision curve analysis (DCA) were used to assess the model's discrimination, calibration and clinical utility. Results: The identified features of the prediction model included age, body mass index (BMI) and three pelvic anatomic parameters measured by MRI: membranous urethral length (MUL), intravesical prostatic protrusion length (IPPL) and puborectalis muscle width (PMW). The nomogram showed good discrimination with an are under the curve(AUC) of 0.914 (95% CI, 0.865-0.959, p < 0.001). Moreover, good calibration was showed in the model. Lastly, DCA showed that the nomogram was clinically useful. Conclusion: The developed novel nomogram that can predict the possibility for post-prostatectomy patients to recover immediate urinary continence could be used as a counseling tool to explain urinary incontinence to patients after LRP.

Magnetic resonance imaging-based radiomics signature for preoperative prediction of Ki67 expression in bladder cancer.

PURPOSE: The Ki67 expression is associated with the advanced clinicopathological features and poor prognosis in bladder cancer (BCa). We aimed to develop and validate magnetic resonance imaging (MRI)-based radiomics signatures to preoperatively predict the Ki67 expression status in BCa. METHODS AND MATERIALS: We retrospectively collected 179 BCa patients with Ki67 expression and preoperative MRI. Radiomics features were extracted from T2-weighted (T2WI) and dynamic contrast-enhancement (DCE) images. The synthetic minority over-sampling technique (SMOTE) was used to balance the minority group (low Ki67 expression group) in the training set. Minimum redundancy maximum relevance was used to identify the best features associated with Ki67 expression. Support vector machine and Least Absolute Shrinkage and Selection Operator algorithms (LASSO) were used to construct radiomics signatures in training and SMOTE-training sets, and diagnostic performance was assessed by the area under the curve (AUC) and accuracy. The decision curve analyses (DCA) and calibration curve and were used to investigate the clinical usefulness and calibration of radiomics signatures, respectively. The Kaplan-Meier test was performed to investigate the prognostic value of radiomics-predicted Ki67 expression status. RESULTS: 1218 radiomics features were extracted from T2WI and DCE images, respectively. The SMOTE-LASSO model based on nine features achieved the best predictive performance in the SMOTE-training (AUC, 0.859; accuracy, 80.3%) and validation sets (AUC, 0.819; accuracy, 81.5%) with a good calibration performance and clinical usefulness. Immunohistochemistry-based high Ki67 expression and radiomics-predicted high Ki67 expression based on the SMOTE-LASSO model were significantly associated with poor disease-free survival in training and validation sets (all P < 0.05). CONCLUSIONS: The SMOTE-LASSO model could predict the Ki67 expression status and was associated with survival outcomes of the BCa patients, thereby may aid in clinical decision-making.

Dysregulation of tumor microenvironment promotes malignant progression and predicts risk of metastasis in bladder cancer.

BACKGROUND: The tumor microenvironment (TME) is not only a key factor in the malignant progression of cancer but also plays an indispensable role in tumor immunotherapy. As an important regulatory factor in the TME, long non-coding RNAs (incRNA) are important for the development of bladder cancer. The purpose of this study was to explore the molecular mechanism of malignant progression of bladder cancer (BCa) from the perspective of immunology, establish a reliable signature, and evaluate its effect on prognosis, metastasis, and the effectiveness of immunotherapy. METHODS: The TME was assessed by single-sample gene set enrichment analysis (ssGSEA) in 373 patients with muscle invasive bladder cancer (MIBC) in The Cancer Genome Atlas (TCGA). Combining RNA sequence data from 49 BCa patients in our center, we established TME-related prognostic signatures (TMERPS) based on TME-related immune prognosis genes using weighted gene correlation network analysis, selection operator Cox analysis, minimum absolute shrinkage, and survival analysis. Real-Time Quantitative PCR was used for expression level analysis of related genes. Functional enrichment analysis and nomograms were used to explore the potential impact of TMERPS on the immune system, prognosis, and metastasis. RESULTS: The ssGSEA proved to be an accurate assessment of immune levels in BCa samples. TMERPS was established based on six TME-associated prognostic lncRNAs and was shown to be closely associated with prognosis, metastasis, and immune levels, and to have a significant stratifying effect on the therapeutic efficacy of immune checkpoint inhibitors. Finally, three TMERPS-based nomograms were shown to be effective in predicting prognosis, lymph node metastasis, and distant metastasis in BCa patients. CONCLUSIONS: TMERPS can stratify BCa patients into different risk groups with different prognoses, immunotherapy sensitivity, and risk of metastasis. TMERPS-based nomograms can effectively predict prognosis and metastasis in BCa patients.

Hsa_circ_0004296 inhibits metastasis of prostate cancer by interacting with EIF4A3 to prevent nuclear export of ETS1 mRNA.

BACKGROUND: Circular RNAs (circRNAs) have been shown to play vital biological functions in various tumors, including prostate cancer (PCa). However, the roles of circRNAs in the metastasis of PCa remain unclear. In the present study, differentially expressed circRNAs associated with PCa metastasis were screened using high-throughput RNA sequencing, from which hsa_circ_0004296 was identified. METHODS: Quantitative real-time PCR (qRT-PCR) was used to detect the expression of circ_0004296 in PCa tissues and adjacent normal tissues as well as in blood and urine. Gain and loss of function experiments were performed to investigate the function of circ_0004296 in PCa. Bioinformatics analyses, RNA pull-down assay, and mass spectrometry were conducted to identify RNA-binding proteins. RNA immunoprecipitation and RNA and protein nuclear-cytoplasmic fractionation were performed to investigate the underlying mechanism. A xenograft mouse model was used to analyze the effect of circ_0004296 on PCa growth and metastasis in vivo. RESULTS: The expression of circ_0004296 was decreased in PCa tissues, blood, and urine, which was negatively associated with metastasis. Furthermore, gain and loss of function experiments in vitro and in vivo showed that circ_0004296 inhibited the proliferation, migration, invasion, and epithelial-mesenchymal transition of PCa cells. Mechanistically, circ_0004296 regulated host gene ETS1 expression at the post-transcriptional level. EIF4A3 was identified and confirmed as the downstream binding protein of circ_0004296. EIF4A3 expression was significantly upregulated in PCa tissues and associated with PCa metastasis. Silencing EIF4A3 suppressed PCa cell proliferation, migration, invasion, and EMT. CONCLUSIONS: Circ_0004296 overexpression efficiently inhibited ETS1 mRNA nuclear export by promoting EIF4A3 retention in the nucleus, leading to the downregulation of ETS1 expression and suppression of PCa metastasis; thus, circ_0004296 might be a potential biomarker and therapeutic target for patients with PCa.

Construction and Validation of a Novel Eight-Gene Risk Signature to Predict the Progression and Prognosis of Bladder Cancer.

The progression from non-muscle-invasive bladder cancer (NMIBC) to muscle-invasive bladder cancer (MIBC) increases the risk of death. It is therefore important to find new relevant molecular models that will allow for effective prediction of the progression and prognosis of bladder cancer (BC). Using RNA-Sequence data of 49 BC patients in Shanghai tenth people's hospital (STPH) and weighted gene co-expression network analysis methods, a co-expression network of genes was developed and three key modules associated with malignant progression were selected. Based on the genes in three key modules, an eight-gene risk signature was established using univariate Cox regression and the Least absolute shrinkage and selection operator Cox model in The Cancer Genome Atlas Program (TCGA) and validated in validation sets. Subsequently, a nomogram based on the risk signature was constructed for prognostic prediction. The mRNA and protein expression levels of eight genes in cell lines and tissues were further investigated. The novel eight-gene risk signature was closely related to the malignant clinical features of BC and could predict the prognosis of patients in the training dataset (TCGA) and four validation sets (GSE32894, GSE13507, IMvigor210 trial, and STPH). The nomogram showed good prognostic prediction and calibration. The mRNA and protein expression levels of the eight genes were differentially expressed in cell lines and tissues. In our study, we established a novel eight-gene risk signature that could predict the progression and prognoses of BC patients.

A Genomic-Clinicopathologic Nomogram for the Prediction of Lymph Node Invasion in Prostate Cancer.

BACKGROUND: Lymph node status is important for treatment decision making in prostate cancer (PCa). We aimed to develop a genomic-clinicopathologic nomogram for the prediction of lymph node invasion (LNI) in PCa. METHODS: Differentially expressed genes between LNI and non-LNI PCa samples were identified in the Cancer Genome Atlas database. Univariate Cox regression analysis and minimum redundancy maximum relevance were performed for gene selection. The synthetic minority oversampling technique (SMOTE) was conducted to balance the minority group (LNI group). Machine learning models were constructed in the training set and assessed in the validation set. Univariable logistic regression and multivariable logistic regression were applied to build a nomogram. Furthermore, the RNA-sequence data from our center were used to validate the expression levels of hub genes between five matched primary PCa and the corresponding LNI samples. RESULTS: The 37-gene-based support vector machine (SVM) model had the optimal synthesized performance in the SMOTE-balanced training (area under the curve (AUC): 0.947) and validation (AUC: 0.901) sets. Incorporating the SVM-based risk score and the Gleason grade, the genomic-clinicopathologic nomogram demonstrated good prediction and calibration both in the SMOTE-balanced training (AUC: 0.946) and validation (AUC: 0.910) sets. The dysregulated expression of hub genes between PCa and LNI samples was also validated. CONCLUSION: The proposed nomogram combining the 37-gene-based SVM model with the Gleason grade had the potential to preoperatively predict LNI in PCa. Some of the hub genes should be prioritized for functional studies and mechanistic analyses.

Combining Multiparametric MRI Radiomics Signature With the Vesical Imaging-Reporting and Data System (VI-RADS) Score to Preoperatively Differentiate Muscle Invasion of Bladder Cancer.

BACKGROUND: The treatment and prognosis for muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC) are different. We aimed to construct a nomogram based on the multiparametric MRI (mpMRI) radiomics signature and the Vesical Imaging-Reporting and Data System (VI-RADS) score for the preoperative differentiation of MIBC from NMIBC. METHOD: The retrospective study involved 185 pathologically confirmed bladder cancer (BCa) patients (training set: 129 patients, validation set: 56 patients) who received mpMRI before surgery between August 2014 to April 2020. A total of 2,436 radiomics features were quantitatively extracted from the largest lesion located on the axial T2WI and from dynamic contrast-enhancement images. The minimum redundancy maximum relevance (mRMR) algorithm was used for feature screening. The selected features were introduced to construct radiomics signatures using three classifiers, including least absolute shrinkage and selection operator (LASSO), support vector machines (SVM) and random forest (RF) in the training set. The differentiation performances of the three classifiers were evaluated using the area under the curve (AUC) and accuracy. Univariable and multivariable logistic regression were used to develop a nomogram based on the optimal radiomics signature and clinical characteristics. The performance of the radiomics signatures and the nomogram was assessed and validated in the validation set. RESULTS: Compared to the RF and SVM classifiers, the LASSO classifier had the best capacity for muscle invasive status differentiation in both the training (accuracy: 90.7%, AUC: 0.934) and validation sets (accuracy: 87.5%, AUC: 0.906). Incorporating the radiomics signature and VI-RADS score, the nomogram demonstrated better discrimination and calibration both in the training set (accuracy: 93.0%, AUC: 0.970) and validation set (accuracy: 89.3%, AUC: 0.943). Decision curve analysis showed the clinical usefulness of the nomogram. CONCLUSIONS: The mpMRI radiomics signature may be useful for the preoperative differentiation of muscle-invasive status in BCa. The proposed nomogram integrating the radiomics signature with the VI-RADS score may further increase the differentiation power and improve clinical decision making.